Reputation: 3340
Is there some way for taking input from a file other than using for loop ? I am using,
data = fileinput.input()
c = [int(i) for i in data]
c.sort()
But for very large amount of data, it takes too long to process. input is of the format,
58457907
37850775
19743393
70718573
....
Upvotes: 0
Views: 156
Reputation: 104092
If I create a 'large' file:
from random import randint
with open('/tmp/nums.txt', 'w') as fout:
a,b=100002/10000, 100002*10000
for i in range(100002):
fout.write('{}\n'.format(randint(a,b)))
I can read it, convert it to integers, and sort in place the data thus:
with open('/tmp/nums.txt') as fin:
nums=[int(e) for e in fin]
nums.sort()
The total time for this operation is 50 ms on my computer. Is 50 ms a long time?
With a more formal timing:
def f1():
with open('/tmp/nums.txt') as fin:
nums=[int(e) for e in fin]
nums.sort()
return nums
def f2():
with open('/tmp/nums.txt') as fin:
return sorted(map(int, fin))
def f3():
with open('/tmp/nums.txt') as fin:
nums=list(map(int, fin))
nums.sort()
return nums
if __name__ =='__main__':
import timeit
import sys
if sys.version_info.major==2:
from itertools import imap as map
result=[]
for f in (f1, f2, f3):
fn=f.__name__
fs="f()"
ft=timeit.timeit(fs, setup="from __main__ import f", number=3)
r=eval(fs)
result.append((ft, fn, str(r[0:5])+'...'+str(r[-6:-1]) ))
result.sort(key=lambda t: t[0])
for i, t in enumerate(result):
ft, fn, r = t
if i==0:
fr='{}: {:.4f} secs is fastest\n\tf(x)={}\n========'.format(fn, ft, r)
else:
t1=result[0][0]
dp=(ft-t1)/t1
fr='{}: {:.4f} secs - {} is {:.2%} faster\n\tf(x)={}'.format(fn, ft, result[0][1], dp, r)
print(fr)
You can see that the differences between these are not huge (except for PyPy where f3 clearly has an advantage):
Python 2.7.8:
f3: 0.2630 secs is fastest
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
========
f2: 0.2641 secs - f3 is 0.41% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
f1: 0.2779 secs - f3 is 5.67% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
Python 3.4.1:
f2: 0.1873 secs is fastest
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
========
f3: 0.1881 secs - f2 is 0.41% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
f1: 0.2071 secs - f2 is 10.59% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
PyPy:
f3: 0.1300 secs is fastest
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
========
f2: 0.1428 secs - f3 is 9.81% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
f1: 0.2223 secs - f3 is 70.94% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
PyPy3:
f3: 0.2483 secs is fastest
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
========
f2: 0.2588 secs - f3 is 4.23% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
f1: 0.2878 secs - f3 is 15.88% faster
f(x)=[3025, 18834, 19637, 29124, 42088]...[999964829, 999970030, 999984585, 1000005692, 1000010131]
Upvotes: 4
Reputation: 180522
Using readlines
and map
using with
to open the file seems more efficient on a test of a file with 200 lines.
In [3]: %%timeit
with open("in.txt",'rb') as f:
lines = map(int,f)
lines.sort()
...:
10000 loops, best of 3: 183 µs per loop
In [5]: %%timeit
data = fileinput.input("in.txt")
c = [int(i) for i in data]
c.sort()
...:
1000 loops, best of 3: 443 µs per loop
Upvotes: 3